The Doppler radar map on the left shows a typical display augmented by data from cars! How simple. How amazingly powerful!

“A distinct change in wind direction is observed by the automobile as it approaches the storm center, indicating inflows at ground level characteristic of tornado formation. This information is not available from either the fixed weather stations or the Doppler radar. Automobiles are already equipped with useful temperature and pressure sensors; simple rain and wind sensors could be readily added. Drawing data from the community of millions of vehicles on the road would complement our centralized satellite and ground-based weather data sources, enabling us to forecast development of severe weather and micro-weather with unprecedented accuracy.

Google’s new traffic data is already integrating realtime data from moving vehicles to enhance the utility of its product. Why not do the same to help initialize our weather models?

I can’t tell you how many times I’ve talked with meteorologist friends about data initialization being a weak link in weather prediction. We just have too few observations to use. It would seem for short term predictions a dense carpet of additional observations might greatly increase our accuracy.

This still doesn’t put more sensors in the oceans or other inhospitable places, so the global and extended range implications seem minor. For thunderstorms, tornadoes and even the development of winter storms this could make a huge difference.